Sales and Trading

There are many trends worth watching in the financial industry. One example is the growth of outsourced trading, which occurs when a company provides trading services (e.g. trade execution, research, access to international markets) to other firms such as hedge funds. “Outsourced trading is no longer a taboo topic. In fact, it is now firmly a part of the institutional trading ecosystem,” said Dragan Skoko, head of outsourced trading and xBK at BNY Mellon, in an article about the trend in The TRADE. Companies are outsourcing trading (or using a hybrid model that outsources some of its trading) to improve operational efficiencies, pursue growth while reducing costs, address regulatory change and compliance challenges, and fill technology and staffing needs that can’t be met in house. Other noteworthy trends include the integration of machine learning, artificial intelligence (including generative AI), and blockchain technology into trading platforms, the growing popularity of cryptocurrencies, the continuing decline of trading commissions, and the increasing use of alternative data.

Generative Artificial Intelligence is Changing Trading in the Financial Industry

The financial sector has used traditional artificial intelligence for years to classify data, for process automation, and to uncover hidden patterns and predict events. But the emergence of generative artificial intelligence will have an even bigger effect. Generative AI is a form of machine learning algorithms that can be used to create new content (including text, simulations, videos, images, audio, and computer code), as well as analyze and organize vast amounts of data and other information. Examples of generative AI include ChatGPT, Gemini, and DALL-E. “This new wave of AI promises to reshape the industry, at a steady and incremental rate, by providing new capabilities, revenue opportunities, and cost reductions,” according to S&P Global Ratings. The credit rating agency goes on to predict that “over time, that could tilt the competitive landscape in favor of those banks that best utilize AI’s potential.” The professional services firm Deloitte predicts that the top 14 global investment banks could increase their front-office productivity by as much as 35 percent by using generative AI.

Here are a few current uses of generative AI in the banking sector:

• Wells Fargo is utilizing conversational AI to empower its virtual assistant, called Fargo, as well as using large language models to identify what information clients must provide to regulators.
• Morgan Stanley is developing a service that uses OpenAI’s GPT-4 technology to help employees locate relevant inhouse information, such as data from capital markets and company insights across sectors and regions
• Goldman Sachs is testing generative AI tools to help with code writing and testing.
• Bank of America has a platform (known as Glass) that, according to S&P Global Ratings, helps sales and trading staff “uncover hidden market patterns to anticipate client needs by consolidating market data across asset classes and regions with the bank’s inhouse models and machine learning techniques.’

Many traders believe that AI will play a major role in trading. In 2024, J.P Morgan surveyed 4,010 institutional traders in more than 65 countries regarding a variety of issues, including their opinions on technology. Sixty-one percent cited AI and machine learning as the most influential technologies that will shape the future of trading over the next three years. This was an 8 percent increase in ranked importance from 2023.

“Automation and low-latency trading infrastructure have already morphed trading dramatically, possibly leading to greater market efficiencies, and reduced transaction costs,” according to an article in Deloitte Insights magazine. The authors of the article go on to say the following about the uses of generative AI:

Traders leverage natural language processing and sentiment analysis to analyze markets, generate synthetic data for risk modeling, and optimize trading strategies. We estimate generative AI’s impact on such activities could significantly reduce time to understand market sentiment, catch anomalies, and place orders more easily and at greater scale. In equities trading, generative AI can help traders quickly analyze, summarize company and industry fundamentals, run valuation models, conduct backtest trading strategies, and offer personalized trading recommendations to both institutional and retail clients.

It will be harder to use generative AI in fixed income instruments, currencies, and commodities trading because this type of trading requires complex analysis and valuation, as well as higher systemic risk (which attracts more regulatory scrutiny).

The data analytics firm IDC reports that enterprises invested nearly $16 billion worldwide on generative AI solutions in 2023, and spending is expected to reach $143 billion in 2027 with a compound annual growth rate of 73.3 percent over the 2023-2027 forecast period.

Generative AI is still in the early stages of use and development, and investment banks and other financial industry players are still trying to address ethical issues and security, reputational (Gen AI can sometimes create inaccurate or biased information and conclusions), and operational risks. “It may also alter the dynamics with buy-side clients; as they also embrace this technology, the outputs they are able to generate with greater efficiencies may reduce dependency on the sell-side,” according to Deloitte Insights. “Some clients may want to independently develop their own value streams and turn to banks only for the most high-value-adding services.”

So, what does the growing use of artificial intelligence and generative AI mean for traders? While there will still be jobs for traders, there will be far fewer positions. There will be increasing opportunities for traders who are skilled at programming and software development to create new trading platforms, monitor and troubleshoot AI/machine learning trading systems, and develop data analytics software.

Blockchain Technology Will Increasingly Be Used in Trading and in the Financial Sector

Blockchain is a shared and distributed ledger database that uses advanced cryptography to maintain a continuously-growing list of financial records that cannot be altered. Financial firms are already using blockchain to improve efficiency and the accuracy of financial record-keeping and reporting. “Blockchain in financial trading means transparent pricing, new alternative markets, faster payment processing and immutable transaction recordkeeping,” according to Built In, an online community for startups and tech companies. “Blockchain’s ledger technology is enabling people to trade for lower costs and at faster speeds than ever before.”

The increasing use of blockchain technology will create demand for software developers, programmers, and other computer specialists who are skilled at developing and using this technology. Sales and trading professionals with knowledge of blockchain technology—as well as artificial intelligence, machine learning, and data analysis techniques—will improve their chances of continuing to prosper in the financial industry.

The Growing Popularity of Cryptocurrencies

MotleyFool.com defines cryptocurrency as “an electronic cash system that doesn't rely on central banks or trusted third parties to verify transactions and create new units. Instead, it uses cryptography to confirm transactions on a publicly distributed ledger called the blockchain, enabling direct peer-to-peer payments.” The entire cryptocurrency market had a capitalization of $1.06 trillion in 2023, according to Statista.com, up from $237 billion in 2019. Bitcoin is the most popular type of cryptocurrency. On September 13, 2023, it accounted for 49.1 percent of the total cryptocurrency market cap, according to Slickcharts.com. Other cryptocurrencies with significant market capitalization include Ethereum (18.5 percent), Tether (7.98 percent), and BNB (3.14 percent).

While the public has embraced the buying and selling of cryptocurrency, the financial sector has expressed less interest in general. In 2024, J.P Morgan surveyed 4,010 institutional traders in more than 65 countries regarding a variety of issues. Only 9 percent reported trading crypto/digital coins. Seventy-eight percent of traders surveyed had no plans to trade crypto/digital coins. Twelve percent of respondents planned to trade them within five years.

There is stronger interest in the hedge fund sector. Indexes have been launched to track hedge funds that invest and trade in cryptocurrencies. In December 2017, Hedge Fund Research launched the HFR Blockchain Composite Index and the HFR Cryptocurrency Index to track hedge funds that invest and trade in cryptocurrencies. About 300 hedge funds are focused on cryptocurrency. Total assets under management of crypto hedge funds surveyed by PwC for its Annual Global Crypto Hedge Fund Report 2022 were $4.1 billion in 2021, up 8 percent from 2021. Traditional hedge funds are also investing in cryptocurrencies.

Trading Commissions Continue to Decline

Investment banks, hedge funds, and other financial companies traditionally have earned strong profits from commissions received for facilitating trades for clients. But this has changed in recent years, reducing earnings. Equity commissions dropped 17.5 percent from 2021 to 2022, according to Bloomberg’s 2023 U.S. Institutional Equity Trading Study. Factors that have reduced trading commission fees include:

• The growing popularity of electronic trading, which is less labor intensive, according to Accenture, “has also given rise to low-touch, low-commission discount brokerage models.”
• Deregulation, which has created competition for customers and fueled the end of fixed brokerage commission rates.
• The embrace of low-cost passive fund managers; Accenture reports that passive fund managers have “gained market share held by traditional active asset managers and increased pricing pressure on brokerages by favoring lower-cost execution options that align with their low-cost business models.
• Increasing customer willingness to switch financial institutions in pursuit of lower fees, lower transaction costs, and ease of account access.

To address this loss of revenue, Accenture recommends that investment banks and brokerages “should focus on becoming excellent at what is considered ‘table stakes’ in the trading business—trade execution efficiency. The digital era has not only led to a sea-change in customer expectations, but also brought about technology advancements that innovative banks and brokerages can leverage to redefine their business models at lower cost, faster pace, and with a wider reach than was previously possible.”

The Increasing Use of Alternative Data

More companies are using data analytics tools to collect and study alternative data to obtain investing, operational, or other benefits over their competitors. Alternative data, which is also known as next-generation data, is nontraditional and non-market economic and financial information, such as business performance metrics, online reviews, weather patterns, satellite imagery, consumer spending/lifestyle data (including payments data), and social media trends. In recent years, the collection of alternative data has been supercharged by the use of artificial intelligence, which has increased the speed at which data can be collected and analyzed. “In the scramble for alpha—the financial industry’s term for market advantage—no data set is too obscure as long as some actionable signal can be gleaned,” according to Built In, an online community for startups and tech companies. “Fundamental firms incorporate alt data to help interrogate their existing investment hypotheses, while quants input the alternative stuff into models alongside reams of traditional data. That is, alternative data will always be an ingredient, not the whole stew.” The number of alternative-data providers increased from 20 in 1990 to more than 400 in 2023, according to a report by the Alternative Investment Management Association in collaboration with fintech company SS&C.